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🔥我靠!终于有大公司把AI模型后训练的“魔法”拆成可复现配方了!

🔥我靠!终于有大公司把AI模型后训练的“魔法”拆成可复现配方了!…🔥我靠!终于有大公司把AI模型后训练的“魔法”拆成可复现配方了!…🔥我靠!终于有大公司把AI模型后训练的“魔法”拆成可复现配方了!…

This is a AI post classified by AGK Intelligence as AI research (research), kept by the AI Radar because it carries real work, not commentary.

🔥我靠!终于有大公司把AI模型后训练的“魔法”拆成可复现配方了! 
Amazon团队直接公开从GLM-4.5-Air-Base出发的完整8阶段串行后训练pipeline,数据来源、奖励设计、筛选方法、训练配置、阶段结果全部写清楚,且大量用公开数据、无新增人工标注、无内部蒸馏教师! 他们发现: 1️⃣串行8阶段流水线(每一步继承上一步参数):
SFT → Reasoning RL → Coding RL → Instruction-Following RL → General Agent → Coding Agent → Search Agent → RLHF
从基础能力到高级Agent,从硬可验证奖励逐步过渡到软judge奖励。 2️⃣不造新数据也能大幅提升:大量复用已公开数据集,附录详细标注来源,证明高质量公开数据+合理筛选就能打。 3️⃣核心原则: ▫️多样高质量SFT先打牢能力地板 ▫️难度过滤让RL prompt保持在有效学习区间 ▫️奖励可靠性决定阶段顺序(先硬规则/执行验证,再软LLM judge) ▫️工程与基础设施本身就是配方的一部分 4️⃣效果炸裂:Rufus-Air在多个基准上大幅超越智谱官方后训练的GLM-4.5-Air,与同规模开源模型竞争激烈。 后训练不再是黑箱!这套recipe直接拉高了开源可复现的天花板。 论文链接:https://arxi

Posted by SuSu_酥酥👅 (26.9k followers) 8 h ago · 107 likes · 5.6k views · view the original post on X. Kept by the AI Radar as AI research. Tools mentioned: arXiv.org.

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